Analysis of the SHRP 2 Naturalistic Driving Study Data [S08(B)]

Evaluation of Offset Left-Turn Lanes

Jessica M. HuttonPresentation to MCTRS

August 15, 2013

Research ObjectivesPhase 1• Determine if we can use the NDS dataset to

evaluate gap acceptance behavior at offset left-turn lanes

• Develop and validate a study design to do this

Phase 2• Answer the study questions:

– Do offset left-turn lanes affect turn behavior and gap acceptance?

– What effect does the presence of a vehicle in the opposing left-turn lane have?

• Develop design guidance for offset left-turn lanes2

What is an Offset Left-Turn Lane?

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Left-Turn Lanes and Sight Distance

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Research Activities

IRB approval and Data Sharing Agreement

Identify intersections for

research

Define and refine data request and

receive data

Reduce video data Analyze dataDraw conclusions

and develop recommendations

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IRB and DSA• This research is designed specifically to avoid the

collection or use of personally identifying information of NDS participants.

• We are exempt from IRB approval.• We cannot use the NDS data for any other

research without another DSA, and we cannot share it with third parties.

• If we develop any datasets that could be useful to other researchers, those will be made available to SHRP 2.

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Identifying Intersections• To answer our research questions, we need

intersections with the following characteristics:– Dedicated left-turn lanes– Unsignalized or permissive left-turn signal phasing– No sight limitations due to geometry– Drivers making left turns there

• Among the intersections chosen, we need a variety of offset conditions to observe how changes in offset correlate with changes in gap acceptance behavior

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All NDS data

Trips made through intersections

Intersections with dedicated left-turn lanes

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Signalized

Unsignalized

Neg

ativ

e of

fset

Zer

o of

fset

Pos

itive

offs

etPermissive-only left-turn phasing

Protected/Permissive left-turn phasing

Protected-only left-turn phasingHeavily traveled intersections Highway agencies

can help identify intersections with desired signal phasing

Any of these intersections could be considered for use in analysis

Data Request• Using NDS data to identify study

intersections– CTRE has gathered roadway characteristics information

for many highly traveled routes. They are currently helping to develop a list of intersections for us to evaluate for inclusion in the research, and are providing the following data for each intersection:

• Traffic control (signalized, two-way stop, etc.)

• Number/type of lanes

• AADT of approach legs (to the extent available)

• GPS coordinates

– VTTI created trip maps early in the project to identify the routes with the highest number of trips by NDS participants. The list of intersections provided by CTRE will be narrowed to those with the highest trip counts.

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Data Request• After list of potential study intersections is

developed:– Research team views intersections in Google Earth to

look for desirable characteristics such as:• 90° intersection angle (no skew)

• No significant grade or horizontal curvature on approaches

• Amount of offset of left-turn lanes (need to get a range from negative to positive)

– Research team identifies approaches of interest at each intersection

– Research team provides VTTI with final list of intersections for which data will be requested

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Data Request

• Data request is location based– We provide VTTI with the GPS coordinates of the intersections

we chose to study, and they provided us with forward and rear video, as well as some elements of the time-series data, for any left-turn trips made through that intersection.

– The beginning and end of a trip are defined by proximity to the center of the intersection. A “geofence” is placed at a 500-ft radius boundary around the center of the intersection.

– VTTI helped develop this solution after we had difficulty defining the beginning and end of a trip in terms of time. Trips at a given intersection all begin and end in the same location, and are of various lengths of time depending on how long drivers wait at the intersection and how fast they are driving.

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Using the Data• Our primary data source is the forward and rear

video• A Community Viewer was developed as a tool by

VTTI to view all camera views simultaneously, but this didn’t work well for us.

• In Phase 1, data reduction was manual—we watched forward video and rear video independently and recorded observations in an Excel spreadsheet.

• For Phase 2, we started developing our own viewer to watch the forward and rear video together, and are integrating a data-reduction interface specific to our project. 12

User Interface for Data Reduction

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Using the video data to measure gaps

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Time T0: First opposing through vehicle reaches the center of the intersection after the study vehicle arrives

Time T2: Turn is made by study driver

Rejected Gap = T1 – T0 Accepted Gap = T3 – T1

Time T1: Next opposing through vehicle reaches the center of the intersection

Time T3: First opposing through vehicle reaches the center of the intersection after the study vehicle makes the left turn

T3 is estimated from forward camera or viewed in rear

camera

T0, T1 and T2 are viewed in the forward-facing camera

Data Elements from Video Reduction

• For each turn made by NDS study vehicle:– Time when study vehicle arrives in queue– Time when study vehicle becomes first in queue– Position in queue when study vehicle arrives– Time when turn is made– Signal indication when study vehicle arrives and when

turn is made (also, time when signal indication changes if applicable)

– Light and weather conditions

• For each gap accepted or rejected by NDS or non-NDS driver:– Timestamp for end of each gap– Presence of opposing left-turner and impact on sight distance– Presence of opposing right-turner

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Analysis Approach

Hypotheses to be Tested:• Do different types of offset affect drivers’ gap

acceptance behavior?• Does presence of an opposing left-turn

vehicle affect that gap acceptance behavior?• Do different types of offset affect the rate of

occurrence for erratic maneuvers during left turns?

Statistical Method Used:• Logistic regression analysis

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Phase 1 Summary Statistics

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Unique object ID

(VTTI)Offset type

Number of left-turn maneuvers recorded

Total number of

rejected gaps

Total number

of accepted

gaps

Number of events with a vehicle present in the

opposing left turn ‑lane

NDS vehicles

Non-NDS vehicles No Yes

7Positive

9 2 39 2 20 2113 1 0 4 0 4 019

Zero32 10 87 10 61 36

23 25 1 34 2 31 428 23 14 104 15 81 2033 Negative 3 0 10 1 11 0

Total 93 27 278 30 208 81

Distribution of Gaps by Left-Turning Study Vehicles

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Logistic Regression Models by Offset Type

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Anticipated Phase 2 Research Results

• Design guidance and recommended criteria for offset left-turn lanes

• Recommended updated text for left-turn lane discussion in Chapter 9 of the Green Book

• Useful to traffic safety engineers, design engineers, and planners in state and local highway agencies, as well as consultants and researchers

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